WO2022146015A1

WO2022146015A1 - Method and device for calculating individualized probability of medication side effect

Info

Publication number: WO2022146015A1
Application number: PCT/KR2021/020126
Authority: WO
Inventors: 강민규
Original assignee: 충북대학교병원
Priority date: 2020-12-30
Filing date: 2021-12-29
Publication date: 2022-07-07
Also published as: KR102656669B1; CN116888681A; US20240013930A1; KR20240049792A; KR20220097601A

Abstract

A method for calculating an individualized probability of a medication side effect by means of a computing device according to an embodiment disclosed herein may comprise the steps of: confirming the medication taken by a subject; confirming the subject's experience of a side effect as a result of taking the medication, which was received as an input from the subject; and calculating the probability of the side effect occurring in the subject in relation to the medication on the basis of the experience of the side effect by the subject, wherein each of the steps is performed by the computing device.

Description

Method and Apparatus for Estimating Personalized Probability of Drug Side Effects

The present disclosure relates to a method and an apparatus for estimating a personalized probability of a drug side effect, and more particularly, to a method and an apparatus for calculating an occurrence probability of a drug side effect based on an individual's experience taking a drug.

Individuals are taking medications prescribed by a hospital or taking various medications according to the individual's judgment or the advice of a pharmacist.

Drugs have the potential to cause various side effects to the user, but this is a statistical probability before individuals taking the drug, and the possibility that the side effect actually occurs to individuals taking the drug is different. When taking the same drug multiple times before, the probability of experiencing a side effect when taking the drug at a specific point in time may actually differ from person to person, depending on whether or not the person has experienced side effects in the past.

That is, among different individuals taking the same drug with the same statistical side effect probability, one user may experience the side effect as a result, but the other user may not experience the side effect, and the statistical side effect of a particular component of the drug may occur. Despite the high probability, certain users may have physical conditions that do not cause side effects of the drug.

However, when taking a drug composed of various drugs or taking a variety of drugs for a disease, it is difficult for each individual to know whether the side effect experienced by the drug is caused by the drug or the component contained in the drug. Therefore, there is a problem in that it is difficult to avoid the drug or component that caused the side effect to the individual so as not to experience the side effect again.

When prescribed in a hospital, the doctor can inform the doctor of the side effects experienced by the individual and the doctor can exclude drugs that are likely to cause side effects from the prescription, but there is a problem in that it is difficult to apply to all drugs taken by the individual.

As a prior art, there is a technique that excludes from prescription drugs with side effects experienced by individuals, but as described above, it is difficult for individuals who have taken various drugs to know which side effects occurred with which drugs, and taking drugs other than those prescribed by a doctor. There is a problem in that it is difficult to apply this.

Recently, attempts have been made to calculate the possibility of drug side effects based on individual genes or to calculate the possibility of drug side effects based on individual physiological characteristics, but it is not yet recognized as an official personalized side effect probability technique, and it is economically and methodically This is difficult to access.

Therefore, although it is not scientifically accurate probability corresponding to the gold standard, there is a need for a technology that allows an individual to easily identify a drug with a high probability of causing side effects.

An embodiment of the present disclosure provides a method and apparatus for estimating the probability of occurrence of a drug side effect based on an individual's experience of taking a drug.

Another embodiment of the present disclosure provides a method and apparatus for estimating the probability of occurrence of a personalized drug side effect based on the occurrence or non-occurrence of a side effect when an individual takes a drug.

Another embodiment of the present disclosure provides a method and an apparatus for estimating the probability of occurrence of a drug side effect based on the intensity of the side effect when the individual takes the drug, the previous administration time, and the like.

The problem to be solved by the present invention is not limited to the above-mentioned problems, and other problems and advantages of the present invention not mentioned can be understood by the following description, and more clearly understood by the embodiments of the present invention will be In addition, it will be understood that the problems and advantages to be solved by the present invention can be realized by means and combinations thereof indicated in the claims.

The personalized drug side effect probability calculation method of the computing device according to an embodiment of the present disclosure is a method in which each step is performed by a computing device, the step of checking the drug taken by the subject, It may include the step of confirming the inputted experience of the side effect, and calculating the probability of occurrence of the subject's side effect in relation to the drug based on the subject's experience of the side effect.

The computing device for calculating the personalized drug side effect probability according to an embodiment of the present disclosure includes a processor and a memory that is functionally connected to the processor and stores at least one code executed by the processor, and the memory is executed by the processor confirms the drug taken by the subject, confirms the occurrence of side effects received from the subject according to the subject's taking of the drug, and determines the probability of occurrence of side effects of the subject in relation to the drug based on the subject's experience of side effects You can store the code that causes it to calculate.

The method and apparatus for calculating the probability of occurrence of a drug side effect according to an embodiment of the present disclosure allow an individual to easily identify a drug or a component of the drug that is likely to cause a side effect to themselves.

The method and apparatus for calculating the occurrence probability of a drug side effect according to an embodiment of the present disclosure can prevent secondary damage due to side effects by excluding side effects that may be caused by personally taking drugs.

The method and apparatus for calculating the probability of occurrence of a drug side effect according to an embodiment of the present disclosure may identify a drug or a component of the drug that is highly likely to cause a side effect to the individual from among various drugs taken by an individual.

Effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a diagram illustrating an environment in which a method and an apparatus for calculating the occurrence probability of a drug side effect based on an individual's experience of taking a drug according to an embodiment of the present disclosure are implemented.

2 is a block diagram illustrating a configuration of a user terminal according to an embodiment of the present disclosure.

3 is a block diagram illustrating a configuration of a server device according to an embodiment of the present disclosure.

4 is a flowchart for explaining a method of calculating the probability of occurrence of a drug side effect according to an embodiment of the present disclosure.

5 is a flowchart for explaining a method of calculating the probability of occurrence of a drug side effect according to an embodiment of the present disclosure.

6 is a diagram for briefly explaining drug side effect information of a drug side effect database according to an embodiment of the present disclosure.

7 and 8 are diagrams illustrating an individual's experience of side effects for explaining a method of calculating the probability of occurrence of drug side effects according to an embodiment of the present disclosure.

9 is a diagram illustrating an interface of a user terminal according to an embodiment of the present disclosure.

Hereinafter, the embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings, but the same or similar components are assigned the same reference numbers regardless of reference numerals, and redundant description thereof will be omitted. The suffixes "module" and "part" for components used in the following description are given or mixed in consideration of only the ease of writing the specification, and do not have distinct meanings or roles by themselves. In addition, in describing the embodiments disclosed in the present specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in this specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in the present specification, and the technical idea disclosed herein is not limited by the accompanying drawings, and all changes included in the spirit and scope of the present invention , should be understood to include equivalents or substitutes.

Terms including an ordinal number such as 1st, 2nd, etc. may be used to describe various elements, but the elements are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

When an element is referred to as being “connected” or “connected” to another element, it is understood that it may be directly connected or connected to the other element, but other elements may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that the other element does not exist in the middle.

An environment for implementing a method or apparatus for calculating the occurrence probability of a drug side effect according to an embodiment of the present disclosure will be described with reference to FIG. 1 .

In the present specification, expressions of drug, drug, drug, etc. may be a drug composed of a single component or multiple components, and do not have different meanings.

In the present specification, dosing is a concept including cases of administration in the body in various forms, such as oral administration, administration through injections, administration through patches, skin application of ointments, and injection through nasal or eye mucosa.

The method or apparatus for calculating the probability of occurrence of a drug side effect according to an embodiment of the present disclosure may be implemented in a user terminal or a server device, and in the following description, it is described on the assumption that it is implemented in a server device, but it can be implemented in a user terminal should pay attention to

An environment for implementing the method or apparatus for calculating the occurrence probability of a drug side effect according to an embodiment of the present disclosure may include the user terminal device 100 and the server device 200 . When the database including the statistical side effect probability information of the drug is implemented as a separate device, the drug side effect database device 300 may be included.

The subject who has taken the drug may input the drug that he or she has taken, whether the side effect experienced after taking the drug, and the type of the side effect if it has occurred, through the user terminal 100 .

Referring to FIG. 9 , when a user inputs a drug 910 taken by the user into the user terminal 100 , the server device 200 displays a component including the drug or side effects 920 related to the drug as side effects data. It may be obtained from the base 300 and provided to the user terminal 100 . The user may select a side effect that he or she has experienced from among the side effects provided or that no side effect has occurred, and the server device 200 determines whether or not the selected side effect occurs and the type of side effect included in the drug or drug taken by the user. The probability of occurrence of side effects of the user is updated with respect to the component.

The server device 200 obtains the statistical side effect probability of the drug taken by the user or a component included in the drug from the drug side effect database 300 or a database provided by itself, and is added to the user's corresponding drug or component included in the drug. It is set as the first personalized drug manager's probability for the first time, and the personalized drug side effect probability is recalculated (updated) for each drug taking experience of the user. The server device 200 recalculates the personalized drug side effect probability by reflecting the experience without side effects.

The server device 200 may receive a specific drug or a specific component from the user terminal 100 and provide a personalized drug side effect probability.

The server device 200 may provide this to the user terminal 100 when the probability of an individual side effect for a specific drug exceeds a preset threshold value or exceeds a preset criterion, such as the occurrence of side effects exceeds a preset consecutive number of times.

The user terminal 100 may be provided with a personalized drug side effect probability for a specific drug or a specific component from the server device 200, and may check this when the user purchases a specific drug. Alternatively, when prescribing, dispensing, or selling a drug to a specific patient at a pharmacy or hospital terminal, a personalized drug side effect probability is provided for that specific patient's specific drug or specific ingredient, so that the patient has a high probability of experiencing side effects Drugs can be excluded.

The configuration of the user terminal 100 will be described with reference to FIG. 2 .

The user terminal 100 may include a communication interface for performing communication with the server device 200 .

The communication interface may include a wireless communication unit or a wired communication unit.

The wireless communication unit may include at least one of a mobile communication module, a wireless Internet module, a short-range communication module, and a location information module.

The mobile communication module includes technical standards or communication methods for mobile communication (eg, GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), CDMA2000 (Code Division Multi Access 2000)), EV-DO ( Enhanced Voice-Data Optimized or Enhanced Voice-Data Only), Wideband CDMA (WCDMA), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term (LTE-A) Evolution-Advanced), etc.), transmits and receives radio signals to and from at least one of a base station, an external terminal, and a server on a mobile communication network.

The wireless Internet module refers to a module for wireless Internet access, and may be built-in or external to the user terminal 100 . The wireless Internet module is configured to transmit and receive wireless signals in a communication network according to wireless Internet technologies.

As wireless Internet technology, for example, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance), WiBro (Wireless Broadband), WiMAX (World Interoperability for Microwave Access), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A), and the like.

The short-range communication module is for short-range communication, and includes Bluetooth™, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, and Near Field (NFC). Communication), Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus) technology may be used to support short-distance communication.

The location information module is a module for acquiring the location (or current location) of the user terminal 100 , and a representative example thereof includes a Global Positioning System (GPS) module or a Wireless Fidelity (WiFi) module. For example, if the terminal utilizes a GPS module, it may acquire the location of the user terminal 100 using a signal transmitted from a GPS satellite.

In an embodiment, the user terminal 100 may include an input unit for inputting the user's drug type, side effect type, and the like.

The input unit may include a microphone for receiving an audio signal and a user input unit for receiving information from a user.

The user input unit may include a mechanical input means (or a mechanical key, a button, a dome switch, a jog wheel, a jog switch, etc.) and a touch input means. As an example, the touch input means consists of a virtual key, a soft key, or a visual key displayed on the touch screen through software processing, or a part other than the touch screen. It may be made of a touch key (touch key) disposed on the.

In an embodiment, the user terminal 100 may include an output unit for transmitting information to the user.

The output unit is for generating an output related to visual, auditory or tactile sense, and may include at least one of a display unit, a sound output unit, and an optical output unit.

The display unit displays (outputs) information processed by the user terminal 100 . For example, the display unit may display a drug provided from the server device 200 in relation to the drug taken by the user or the type of side effects of components included in the drug.

The sound output unit may include at least one of a receiver, a speaker, and a buzzer.

The user terminal 100 may include an interface unit that serves as a passage with various types of external devices connected to the user terminal 100 . The interface unit includes a wired/wireless data port, a memory card port, a port for connecting a device equipped with an identification module, an audio I/O (Input/Output) port, a video I It may include at least one of an /O (Input/Output) port and an earphone port.

A configuration of the server device 200 according to an embodiment of the present disclosure will be described with reference to FIG. 3 .

The server device 200 includes the subject's body information, a diagnosis name (which may be a diagnostic code) when prescribing the subject's drug, the type of drug taken or the type of component included in the drug, the dose and time information of each drug, each When taking a drug, it is possible to store whether or not any side effects experienced or the type of side effects.

The server device 200 may store the drug or statistical side effect information of the components included in the drug, and the component information of the drug.

The server device 200 may store medical treatment information including a patient's diagnosis disease name (which may be a diagnosis code), prescription information, or body information.

The information stored by the server device 200 may be implemented as an external separate database or may be implemented as a storage device 240 that is a part of the server device 200 .

The server device 200 is based on the type of drug the user has taken, whether side effects occur, and the type of side effects, provided from the user terminal 100 through the communication interface 230, and is based on the component information of the drug and the drug or ingredients included in the drug. Using the statistical side effect information, the processor 210 may calculate the user's personalized drug side effect probability.

The processor 210 of the server device 200 may calculate the user's personalized drug side effect probability based on the occurrence as well as the non-occurrence of side effects after the user takes the drug, and in this case, the user's personalized drug side effect probability Algorithms for calculating ? can be applied differently.

The algorithm for estimating the user's personalized drug side effect probability may be implemented in hardware, software, or a combination of hardware and software. can be stored in

A method of calculating a personalized drug side effect probability according to an embodiment of the present disclosure will be described with reference to FIG. 4 .

As previously premised, the method for estimating the personalized drug side effect probability can be implemented in the user terminal, but the following description is based on the assumption that it is implemented in the server device.

The server device 200 checks the medication taken by the user input by the user in the user terminal 100 (S110). The drug taken by the user may be a drug composed of a single component or a drug composed of a plurality of components, and may be a plurality of drugs taken at the same time or within a predetermined time. The drug may be a product name input through a user input, or by recognizing a product name on a product packaging paper or by recognizing a code such as a QR code on a product packaging paper through the camera device of the user terminal 100 . In addition, the server device 200 may check a diagnosis name or a diagnosis code printed on a prescription in a similar manner, or may check a diagnosis name or a diagnosis code by accessing a separate medical information system (OCS, HIS, EMR, etc.).

The server device 200 may check whether the user has side effects according to the taking of the drug or the side effects experience including the type of side effects (S120).

The server device 200 calculates the probability of occurrence of side effects of the user for the individual medications taken based on the user's experience of side effects (S130). When the user first takes the drug, the server device 200 obtains a statistical side effect probability as shown in FIG. 6 of the drug or a component included in the drug from the database, and determines the user's basic side effect probability for the drug The probability of drug side effects is calculated based on the user's experience of side effects set and confirmed.

The side effect experience includes the non-occurrence of side effects, and the server device 200 calculates the drug side effect probability based on the user's side effects experience by reflecting the user's experience that side effects do not occur after taking a specific drug. Therefore, the server device 200 includes the occurrence or non-occurrence of side effects after taking the drug, that is, whenever the user experiences taking the same drug or the experience of taking the drug containing the same component is input. For all experiences, the probability of occurrence of side effects of the user is updated with respect to the drug or a component included in the drug.

The server device 200 applies different algorithms to the experience of occurrence or non-occurrence of side effects after the user takes the drug to calculate the probability of occurrence of side effects of the user with respect to the corresponding drug, which will be described in detail below.

A detailed method ( S130 ) of calculating a personalized drug side effect probability according to an embodiment of the present disclosure will be described with reference to FIG. 5 .

The server device 200 applies different algorithms to the experience of occurrence or non-occurrence of side effects after the user takes the drug to calculate the probability of occurrence of side effects of the user with respect to the corresponding drug, and when no side effects occur It is possible to reduce the probability of occurrence of side effects of the user with respect to the drug or component of the drug (S132).

In this case, the server device 200 may reduce the increase or decrease in the probability of occurrence of side effects of the user for each component when a drug composed of a complex component or a plurality of drugs is taken. In one embodiment, in the case of taking several drugs at the same time, the algorithm for increasing or decreasing the probability of a specific side effect includes a case in which the probability of a specific side effect is increased or decreased equally by dividing by the number of drugs taken, or a weight is applied to the probability of occurrence of a previous side effect and reflected.

When a user first takes a specific drug and no side effects occur, the server device 200 acquires a statistical side effect probability as shown in FIG. 6 and sets it as the user's basic side effect probability for the corresponding drug. For example, referring to FIG. 6 , the probability of occurrence of a statistical side effect for symptom 1 of component A is 10%, and the probability of occurrence of a statistical side effect for symptom 2 is 5%. Thereafter, the server device 200 may multiply the basic side effect probability by a preset disincentive constant that reflects the user's experience of not generating side effects, and the disincentive constant may be less than 1 and may be determined experimentally.

For example, when the inverse compensation constant is 0.5, when the user first takes the drug containing component A and component B, and no side effect occurs, the server device 200 determines the symptom 1 for component A of the user. 5% (=10% × 0.5) chance of adverse event occurrence, 2.5% (=5% × 0.5) chance of adverse event occurrence of symptom 2, and 10% (=20% × 0.5) chance of adverse event occurrence for symptom 1 for component B ) can be calculated as

After that, if side effects do not occur again by taking the same drug, the server device 200 determines the user for each symptom of components A and B using the same inverse compensation constant based on the previously calculated probability of occurrence of side effects of the user. It is possible to recalculate (update) the probability of occurrence of side effects.

A method of calculating a user's side effect probability when a side effect occurs will be described with reference to FIGS. 5 and 7 ( a ).

When the user of FIG. 7 (a) first takes a specific drug containing components A and B, and side effects occur, the server device 200 may check the user's disease (S133). The server device 200 may check prescription information in which the patient's disease code is recorded in an Electronic Medical Record (EMR) server or through a user's input. The EMR server is a concept including a medical record management server managed by a public institution, as well as a medical record management or delivery server managed by a private institution to share or deliver the medical records of each hospital. As described above, the user may recognize or directly input the disease code printed on the prescription through the camera device of the user terminal 100 from the prescription.

The server device 200 may check the symptoms of the user's disease (S134), obtain the statistical side effect probability of the drug or the drug taken by the patient as shown in FIG. 6, and compare them with each other (S135). When the symptoms of the user's disease and the side effects of the drug taken are the same, the server device 200 may not reflect the corresponding side effect experience in calculating the user's drug side effect probability. Accordingly, it is possible to exclude a case in which the user incorrectly calculates the probability of a side effect by mistaking the symptom of a disease as the occurrence of a side effect due to taking the drug.

When the symptoms of the user's disease and the side effects of the medication are different from each other, the server device 200 may increase the probability of occurrence of the side effects of the user for each component of the medication taken (S136).

When a user takes a specific drug for the first time and side effects do not occur, the server device 200 obtains a statistical side effect probability as shown in FIG. 6 and sets it as the user's basic side effect probability for the corresponding drug, and then the server device 200 ) may be multiplied by a preset incentive constant that reflects the user's experience in generating side effects to the basic side effect probability, and the reward constant may be greater than 1 and may be determined experimentally.

For example, when the compensation constant is 1.5, a case in which symptoms 1 and 2 occurs after the user of FIG. 7 (a) first takes a drug containing component A and component B will be described. The server device 200 increases the probability of occurrence of side effects of symptom 1 for component A by 15% (=10% × 1.5), and the probability of occurrence of side effects of symptom 2 for component A by 7.5% (=5% × 1.5), The probability of occurrence of the side effect of symptom 1 for component B can be estimated as 30% (=20% × 1.5). Since symptom 2 is not a statistical side effect of component B, the probability of occurrence of side effects may not be calculated.

After a user, such as the user of FIG. 7(a), takes the same drug containing component A and component B again, or takes another drug containing component A and component B, as shown in FIG. 7(b), symptom 1 is The method of recalculating (updating) the probability of drug side effects for the case where symptom 2 has not occurred will be described.

When the compensation constant is 1.5 and the inverse compensation constant is 0.5, when the user of FIG. 7(b) takes the drug containing component A and component B again, symptom 1 occurs and symptom 2 does not occur to be. The server device 200 may update the drug side effect probability by applying the inverse compensation constant and the compensation constant to the user's stored side effect probability for component A and component B.

For example, the server device 200 increases the probability of occurrence of the side effect of symptom 1 for component A by 22.5% (=15% × 1.5), and the probability of occurrence of the side effect of symptom 2 for component A by 3.75% (=7.5% × 0.5) ), the probability of occurrence of the side effect of symptom 1 for component B can be estimated as 45% (=30% × 1.5). Since symptom 2 is not a statistical side effect of component B, the probability of occurrence of side effects may not be calculated.

Again, it will be described that the user of FIG. 7(b) updates the drug side effect occurrence probability after taking another drug containing component A. For the case where symptom 1 occurs and symptom 2 does not occur as shown in FIG. 8 (b) after a user, such as the user of FIG. Methods for reestimating (updating) the probability of adverse drug reactions are described.

By applying the reward constant 1.5 to the personalized side effect probability of 22.5% for symptom 1 of component A stored in advance for the current user 'A', the personalized side effect probability can be updated to a side effect probability of 33.75%, and the pre-stored component A By applying the inverse reward constant 0.5 to the personalized side effect probability of 3.75% for symptom 2 of , the personalized side effect probability can be updated with a side effect probability of 1.875%. In addition, when component C included in drug 'b' is taken for the first time, the reward constant 1.5 is applied to 10% of the statistical side effect probability for symptom 1 of component C to calculate the personalized side effect probability for component C as 15%. can

In another embodiment, if there is no statistical side effect probability value of the drug or a component included in the drug in the database, the initial value may be set to an arbitrary specific constant value (which may be very small) in terms of implementation. have.

Through the above method, the user can acquire a personalized side effect occurrence probability as the experience of taking different drugs with some overlapping components is accumulated, and determine the drug to avoid based on this.

In another embodiment, the server device 200 may set the compensation constant differently for each component based on the statistical side effect probability of the drug or a component included in the drug.

For example, when the statistical side effect probability of a component included in the drug is as shown in FIG. 6 , the compensation constant for symptom 1 of component A may be set lower than the compensation constant for symptom 1 of component B. Accordingly, it is possible to obtain a personalized side effect occurrence probability by reflecting different statistical probabilities even for a plurality of components having the same side effect symptom.

In another embodiment, the server device 200 may set the compensation constant differently based on the consecutive number of times the user experiences the same side effect after taking the same ingredient.

For example, the server device 200 may set a compensation constant when symptom 1 of component A is continuously experienced a second time to be larger than a compensation constant when symptom 1 of component A is first experienced. Therefore, as the experience of taking different drugs is accumulated, it is possible to obtain a more precisely personalized probability of occurrence of side effects.

In another embodiment, the server device 200 may set the compensation constant differently based on the intensity of the side effect experienced by the user.

*For example, the server device 200 may set the compensation constant when the symptom 1 of the component A is experienced with the intensity 2 to be larger than the compensation constant when the symptom 1 of the component A is experienced with the intensity 1. The server device 200 may provide the user terminal 100 with an interface for selecting the intensity of the side effect experienced by the user. Accordingly, as the experience of taking drugs is accumulated, it is possible to obtain a more precisely personalized probability of occurrence of side effects.

In another embodiment, when the drug blood concentration of the drug previously taken by the user is higher than or equal to a certain level, that is, when it is determined that the drug previously taken remains in the body, the server device 200 is for calculating the probability of side effects of the drug. can be excluded from experience.

For example, the server device 200 checks the time the user previously took the drug containing component A, calculates the blood concentration of component A based on the user's body information set in advance, and the blood concentration is preset In the case of exceeding the standard, even if a side effect occurs, it can be excluded from the experience for estimating the probability of a drug side effect. Therefore, it is possible to exclude that the side effects experience of the drug is increased due to the overlapping experience of side effects due to the previous administration.

The present disclosure described above can be implemented as computer-readable code on a medium in which a program is recorded. The computer-readable medium includes all types of recording devices in which data readable by a computer system is stored. Examples of computer-readable media include Hard Disk Drive (HDD), Solid State Disk (SSD), Silicon Disk Drive (SDD), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. There is this. In addition, the computer may include a processor of a user terminal or a server device.

Meanwhile, the program may be specially designed and configured for the present disclosure, or may be known and used by those skilled in the art of computer software. Examples of the program may include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like.

In the specification of the present disclosure (especially in the claims), the use of the term “above” and similar referential terms may be used in both the singular and the plural. In addition, when a range is described in the present disclosure, each individual value constituting the range is described in the detailed description of the invention as including the invention to which individual values within the range are applied (unless there is a description to the contrary). same as

The steps constituting the method according to the present disclosure may be performed in an appropriate order unless the order is explicitly stated or there is no description to the contrary. The present disclosure is not necessarily limited to the order in which the steps are described. The use of all examples or exemplary terminology (eg, etc.) in the present disclosure is merely for the purpose of describing the present disclosure in detail, and the scope of the present disclosure is limited by the examples or exemplary terms unless defined by the claims. it is not going to be In addition, those skilled in the art will appreciate that various modifications, combinations and changes can be made according to design conditions and factors within the scope of the appended claims or their equivalents.

Accordingly, the spirit of the present disclosure should not be limited to the above-described embodiments, and the scope of the spirit of the present disclosure as well as the claims to be described later are equivalent to or equivalently changed therefrom. will be said to belong to

Claims

A method in which each step is performed by a computing device, the method comprising:

confirming the drug taken by the subject;

confirming the experience of side effects received from the subject according to the subject's taking the drug;

Comprising the step of calculating the probability of occurrence of the side effect of the subject in relation to the drug based on the subject's experience of the side effect,

A method for estimating the probability of a personalized drug side effect on a computing device.
According to claim 1,

The step of calculating the probability of occurrence of the side effect of the subject in relation to the drug,

Including the step of updating the probability of occurrence of the side effect whenever the subject's experience of taking the drug is input,

A method for estimating the probability of a personalized drug side effect on a computing device.
3. The method of claim 2,

The step of updating the probability of occurrence of the side effect comprises:

Comprising the step of updating the probability of occurrence of the side effect based on the experience of non-occurrence of the side effect input after the subject took the drug,

A method for estimating the probability of a personalized drug side effect on a computing device.
3. The method of claim 2,

The step of updating the probability of occurrence of the side effect comprises:

Comprising the step of updating the probability of occurrence of the side effect of the subject by applying different algorithms according to whether the side effect inputted after the subject has taken the drug,

A method for estimating the probability of a personalized drug side effect on a computing device.
According to claim 1,

The step of calculating the probability of occurrence of the side effect of the subject,

identifying a first disease afflicted by the subject;

identifying a first symptom of the first disease; and

Comprising the step of calculating the probability of occurrence of the side effect of the subject based on whether the first symptom and the side effect match,

A method for estimating the probability of a personalized drug side effect on a computing device.
6. The method of claim 5,

The step of calculating the probability of occurrence of the side effect of the subject based on whether the first symptom and the side effect match,

when the first symptom and the side effect do not match, identifying at least one component included in the drug;

checking whether the side effects of the first component included in the drug obtained from the drug database match the side effects input by the subject; and

When the side effect information of the first component and the side effect of the subject match, comprising the step of increasing the probability of occurrence of the side effect for the first component of the subject,

A method for estimating the probability of a personalized drug side effect on a computing device.
7. The method of claim 6,

The step of increasing the probability of occurrence of the side effect for the first component of the subject,

Comprising the step of increasing the probability of occurrence of the side effect for the first component of the subject based on the statistical probability of the side effect of the first component contained in the drug obtained from the drug database,

A method for estimating the probability of a personalized drug side effect on a computing device.
7. The method of claim 6,

The step of increasing the probability of occurrence of the side effect for the first component of the subject,

increasing the probability of occurrence of the side effect for the first component in the subject based on a consecutive number of times the subject experiences the occurrence of the side effect for the first component;

A method for estimating the probability of a personalized drug side effect on a computing device.
7. The method of claim 6,

The step of increasing the probability of occurrence of the side effect for the first component of the subject,

confirming the intensity of the side effect input by the subject; and

increasing the probability of occurrence of the side effect for the first component in the subject based on the intensity of the side effect;

A method for estimating the probability of a personalized drug side effect on a computing device.
6. The method of claim 5,

The step of calculating the probability of occurrence of the side effect of the subject based on whether the first symptom and the side effect match,

when the first symptom and the side effect do not match, identifying at least one component included in the drug;

checking whether the side effects of the first component included in the drug obtained from the drug database match the side effects input by the subject; and

Calculate the drug blood concentration due to the previous dose of the first ingredient based on the time elapsed from the time when the subject previously took the drug containing the first ingredient and the subject's body information, and the drug blood concentration Comprising the step of calculating the probability of occurrence of the side effect of the subject based on

A method for estimating the probability of a personalized drug side effect on a computing device.
According to claim 1,

The step of calculating the probability of occurrence of the side effect of the subject,

When it is input from the subject that there is no occurrence of the side effect according to the taking of the drug, reducing the probability of occurrence of the side effect of the subject with respect to at least one component included in the drug,

A method for estimating the probability of a personalized drug side effect on a computing device.
processor; and

It is functionally connected to the processor and includes a memory in which at least one code executed by the processor is stored,

The memory, when executed in the processor, causes the processor to check the medication taken by the subject, check the occurrence of a side effect received from the subject according to the subject's taking the medication, and respond to the subject's experience of the side effect. storing a code that causes to calculate the probability of occurrence of a side effect of the subject in relation to the drug based on,

computing device.
13. The method of claim 12,

the memory further stores code that, when executed in the processor, causes the processor to update the probability of occurrence of the side effect whenever the subject's experience of taking the medicament is input;

computing device.
14. The method of claim 13,

The memory is a code that, when executed in the processor, causes the processor to update the probability of occurrence of the side effect of the subject by applying different algorithms according to whether the side effect inputted by the subject after taking the drug occurs to save more,

computing device.
13. The method of claim 12,

the memory further stores code that, when executed in the processor, causes the processor to calculate a probability of occurrence of the side effect in the subject based on whether the side effect matches a first symptom of a first disease afflicted by the subject doing,

computing device.
16. The method of claim 15,

When the memory is executed in the processor, the processor causes the first symptom and the side effect to not match, and when the side effect information of at least one component included in the drug matches the side effect of the subject, the subject's causing an increase in the probability of occurrence of the side effect on the first component;

computing device.
13. The method of claim 12,

When the memory is executed in the processor, when it is input by the processor that there is no occurrence of the side effect according to the taking of the drug from the subject, the occurrence of the side effect of the subject for at least one component included in the drug further storing the code causing to reduce the probability,

computing device.